Triple
T33886982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | fishing port of Essaouira |
E868655
|
entity |
| Predicate | hasTypicalVesselColor |
P199071
|
FINISHED |
| Object | blue |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: blue | Statement: [fishing port of Essaouira, hasTypicalVesselColor, blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalVesselColor Context triple: [fishing port of Essaouira, hasTypicalVesselColor, blue]
-
A.
hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
-
B.
hullColor
Indicates the color attribute assigned to the outer surface (hull) of an object, typically a vehicle or vessel.
-
C.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
isVesselFor
Indicates that one entity functions as a container or medium specifically used to hold, carry, or convey another entity.
-
E.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f34996761c8190864e42f7c9cf215b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff1d85441c8190931e758685a269f7 |
completed | May 9, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_69ff1d186cc48190b315c61e23de6551 |
completed | May 9, 2026, 11:40 a.m. |
| PDg | Predicate description generation | batch_69ff1d8394988190acf163a07acad200 |
completed | May 9, 2026, 11:41 a.m. |
Created at: May 1, 2026, 1:48 a.m.